This repository contains experiments, labs, and prototypes developed on Databricks to explore the integration of Data, Machine Learning, and AI technologies. The goal is to provide practical examples, reusable assets, and end-to-end workflows for learning, prototyping, and deploying solutions in Databricks environments.
- Building a Knowledge Assistant with Agent Bricks on Databricks: Labs and code for creating a Knowledge Assistant using Agent Bricks.
- Databricks AI-BI Genie: Experiments integrating AI/BI Genie for conversational dashboards and augmented analytics.
- How to create a Multi Agent System with Databricks: Prototypes and guides for building multi-agent systems on Databricks.
- Model Fine Tuning: Notebooks and assets for ML model fine-tuning experiments.
Additional content will be added progressively, aligned with the editorial plan of technical articles on Databricks, Azure, and AI.
- A Databricks workspace (Community Edition or Enterprise).
- Python 3.9+
- Installed dependencies (see requirements.txt if available, otherwise install directly inside Databricks clusters).
- Clone this repository:
git clone https://github.com/alessandro9110/Databricks-Experiments.git cd Databricks-Experiments - Import notebooks into your Databricks workspace (via the Databricks UI or CLI).
- Attach a cluster and run the experiments step by step.
This repository complements a series of Medium articles and technical blogs on Databricks and AI:
- How to Turn a Databricks Dashboard into a Conversational Assistant Using AI/BI Genie
- Building a Knowledge Assistant with Agent Bricks on Databricks
- Creating Autonomous Agents with Genie and Mosaic AI Agent Framework (in progress)
Contributions, suggestions, and feedback are welcome! Please open an issue or submit a pull request.
This project is licensed under the Apache 2.0 License.